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ACEsuit / mace

MACE - Fast and accurate machine learning interatomic potentials with higher order equivariant message passing.
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Can we use pretrain model (mace_mp) and retrain with our configurations? #308

Closed Amitcuhp closed 5 months ago

Amitcuhp commented 5 months ago

I am curious to know if we can use mace_mp model and start from the epoch given and retrain with new configurations?

Is it possible?

!

davkovacs commented 5 months ago

Yes, it is implemented in the foundations branch: https://github.com/ACEsuit/mace/tree/foundations

you can select "small", "medium" and "large" models and it will automatically select the right hypers, no need to specify them. Here is an example for finetuning the small model:

mace_run_train ^ --name="MACE" ^ --foundation_model="small" ^ --train_file="D:\Work\mace_mp\mp_traj_combined_1p.xyz" ^ --valid_fraction=0.01 ^ --test_file="D:\Work\mace_mp\mp_traj_combined_1p.xyz" ^ --energy_weight=1.0 ^ --forces_weight=1.0 ^ --E0s="average" ^ --lr=0.01 ^ --error_table="PerAtomMAE" ^ --scaling="rms_forces_scaling" ^ --batch_size=2 ^ --max_num_epochs=6 ^ --ema ^ --ema_decay=0.99 ^ --amsgrad ^ --default_dtype="float32"^ --device=cuda ^ --seed=3

Amitcuhp commented 5 months ago

That's wonderfull I have also used universal branch in which the loss function is universal.

Thank you for the reply